Microsoft Word - JBIO_Proteins Sequence Alignment

Abstract—Alignment of biological sequences such as DNA, RNA or proteins is one of the most widely used tools in computational bioscience. One of the important research topics of bioinformatics is the multiple proteins sequence alignment. Since the exact methods for MSA have exponential time complexity, the heuristic approaches and the progressive alignment are the most commonly used in multiple sequences alignments. In the progressive alignment strategy, choosing and merging of the most closely (similarly) sequences is one of the important steps. The information theory provides such a similarity measure using the mutual information (MI). In this paper, we propose a progressive alignment strategy modification based on mutual information. To measure this similarity we define a distance between the sequences based on mutual information, and then we construct a distance matrix. The elements of a row of this matrix correspond the distance between a sequence and all other sequences. A guide tree is built using the distance matrix. We obtain preliminary distance matrix without pairwise alignment in the first step. The principle contribution in this paper is the modification of the first step of the basic progressive alignment strategy i.e. the computation of the distance matrix which yields to a new guide tree. Such guide tree is simple to implement and gives a good result's performance. The results of our testing in all dataset BAliBASE 3.0 data base show that the proposed strategy is as good as Clustalw in most cases.